Given the scale and complexity of today's datasets, people face a critical challenge during visual data analysis: an overwhelming number of decisions. These decisions—about what, where, when, and how to visualize data—directly influence the quality of the analysis process and outcomes. For example, a user must decide what attributes to visualize, whether to apply filters, or which chart type best represents the data. WhileAI-powered tools are increasingly available to assist with these decisions, current support often lacks the human-centric adaptability and transparency that users need, leading to biased interpretations, missed insights, and flawed conclusions. In this talk, I will showcase guidance-enriched visual analytics tools where AI-powered systems and human users “guide” each other during analysis. Specifically, I will demonstrate how guidance can (1) help data analysts increase awareness of (un)biased analytic behaviors during visual data analysis, (2) support mapmakers in creating accurate and trustworthy maps, (3) help people author and style data visualizations using natural language, and (4) help everyday web users shop online. I will conclude with some of my thoughts on how a Human-centric AI (unlike today's AI-centric User) enhances human decision-making as well as system learning, championing the vital and inevitable collaboration between humans and AI.